"How about me giving blood for the COVID vaccine and not being able to get vaccinated?" A cognitive interview study on understanding of and agreement with broad consent for future use with cohort participants and guardians in Colombia and Nicaragua

Informed consent (IC) is key to generating and maintaining research participants trust and upholding the ethical principle of autonomy. Broad consent for future use, wherein researchers ask participants for permission to share participant-level data and samples collected within the study for purposes loosely related to the study objectives, is central to enabling ethical data and sample reuse. Ensuring that participants understand broad consent-related language is key in maintaining trust in the study itself and in public health research generally. Therefore, we conducted 52 cognitive interviews with the help of semi-structured interview guides to explore cohort research participants understanding of the broad consent-related language in the University of California at Berkeley template IC form for biomedical research with participants from long-standing infectious disease cohort studies in Nicaragua and Colombia. After the first round of interviews, we used participants explanations to modify the broad consent-related language in the IC template and consequently re-evaluated participants understanding of and agreement with the new consent form. Participants generally supported data and sample sharing but expressed concerns about the intentions of for-profit groups as well as misuse of data or samples. Moreover, they felt uncomfortable not receiving information about incidental findings and results from future studies. Cohort participants did not understand abstract concepts including the collection and reuse of genetic data in either version of the IC. Trust in the research team and the belief that data and sample sharing could lead to new scientific insights and improved treatments were key to participant support for data and sample sharing. The study findings and research participants language to describe broad consent provide essential insights for researchers who want to include broad consent and ethics review committees (ERCs) working to ensure research is conducted in keeping with the ethical principle of respect for persons. Author SummaryThis is the first study to apply cognitive interviewing to evaluate participants understanding of broad consent. We found that cohort participants did not well understand the broad consent-related language in the UCB template IC. When broad consent was reworded with language from the community, difficult to process concepts, like genetic studies, were better understood. Many ethics review committees (ERCs) and universities require researchers to use a template when consenting participants for participation in biomedical research. Our finding that key concepts in the broad consent section of the template, including genetic studies and sample collection, were not well understood suggests that ERCs must allow researchers flexibility to alter IC template language to ensure participant understanding. While, like many ERCs, the University of California at Berkeley (UCB) recommends that researchers not communicate incidental findings, participants did not understand that incidental findings would not be shared and universally wanted to learn about incidental findings. Participants generally believed in the utility of data and sample reuse but expressed concerns about reuse by commercial groups and wanted to better understand who and what the future users were. Participants did not mention privacy as a concern in data and sample sharing. Informing participants about incidental findings and future uses and users is an important part of maintaining trust in data and sample sharing.

Epidemics of chikungunya, Zika, and COVID-19 reveal bias in case-based mapping

Accurate tracing of epidemic spread over space enables effective control measures. We examined three metrics of infection and disease in a pediatric cohort (N {approx} 3,000) over two chikungunya and one Zika epidemic, and in a household cohort (N=1,793) over one COVID-19 epidemic in Managua, Nicaragua. We compared spatial incidence rates (cases/total population), infection risks (infections/total population), and disease risks (cases/infected population). We used generalized additive and mixed-effects models, Kulldorfs spatial scan statistic, and intracluster correlation coefficients. Across different analyses and all epidemics, incidence rates considerably underestimated infection and disease risks, producing large and spatially non-uniform biases distinct from biases due to incomplete case ascertainment. Infection and disease risks exhibited distinct spatial patterns, and incidence clusters inconsistently identified areas of either risk. While incidence rates are commonly used to infer infection and disease risk in a population, we find that this can induce substantial biases and adversely impact policies to control epidemics. Article summary lineInferring measures of spatial risk from case-only data can substantially bias estimates, thereby weakening and potentially misdirecting measures needed to control an epidemic.